The present study, which is one of the longest temporal (two decades) and largest spatial (different parts of India covered) investigations on inversion polymorphism in natural populations of D. ananassae, was undertaken to understand the dynamics of inversion polymorphism in a broad and comprehensive manner. Forty-five natural populations from different ecogeographic regions of the country (covering the regions from Kashmir to Kanniyakumari and Gujarat to Nagaland) were analysed for chromosomal inversions. All the populations show the presence of the three cosmopolitan inversions, frequencies of which vary among the populations analysed. Simple correlations between frequencies of different inversions and regression analysis of inversion frequencies with latitude, longitude and altitude were insignificant. This reinforces the concept of rigid polymorphism in D. ananassae. Genetic divergence (spatial and temporal) at the level of chromosomal polymorphism among natural populations was calculated. Results show spatial divergence but no temporal divergence. Rigid polymorphic systems of D. ananassae did not show long-term directional trends. On the basis of the present study, and after including comparisons with the studies conducted more than two decades ago, the most important conclusion to be drawn is that the three cosmopolitan inversions in D. ananassae segregate within populations at fairly similar frequencies, and the general geographic pattern has remained constant.

To identify transposons that may be of use for mutagenesis we investigated the genetic molecular basis of a case of flower colour variegation in Linaria, a close relative of the model species Antirrhinum majus. We show that this variegation is attributable to an unstable mutant allele of the gene encoding dihydroflavonol-4-reductase, one of the enzymes required for anthocyanin biosynthesis. This allele carries an insertion of a transposon belonging to the CACTA family (Tl1, Transposon Linaria 1) which blocks its expression thus conferring an ivory flower colour phenotype. Tl1 is occasionally excised in dividing epidermal cells to produce clonal patches of red tissue on the ivory background, and in cells giving rise to gametes to generate reversion alleles conferring a fully coloured phenotype. This finding may open the way for targeted transposon-mutagenesis in Linaria, and hence for using this genus in comparative genetic studies.

Effectiveness of marker-assisted selection (MAS) and quantitative trait locus (QTL) mapping using population-wide linkage disequilibrium (LD) between markers and QTLs depends on the extent of LD and how it declines with distance between markers and QTLs in a population. Marker–QTL LD can be predicted from LD between markers. Our previous work evaluated LD measures between multi-allelic markers as predictors of usable LD of multi-allelic markers with QTLs. Since single nucleotide polymorphisms (SNPs) are the current marker of choice for high-density genotyping and LD-mapping of QTLs, the objective of this study was to use LD between multi-allelic markers to predict LD among biallelic SNPs or between SNPs and QTLs. Observable LD between multi-allelic markers was evaluated using nine measures. These included two pooled and standardized measures of LD between pairs of alleles at two markers based on Lewontin's LD measure, two pooled measures of squared correlations between alleles, one standardized measure using Hardy–Weinberg heterozygosities, and four measures based on the chi-square statistic for testing for association between alleles at two loci. The standardized chi-square measure that best predicted usable LD between multi-allelic markers and QTLs, based on our previous work, overestimated usable SNP–SNP or SNP–QTL LD. Instead, three other measures were found to be good predictors of usable SNP–SNP or SNP–QTL LD when LD is generated by drift. Therefore, the LD measure between multi-allelic markers that is best for predicting usable LD in a population depends on the type of markers (i.e. multi-allelic or biallelic) that will eventually be used for QTL mapping or MAS.

A multivariate QTL detection was carried out on fatness and carcass composition traits on porcine chromosome 7 (SSC7). Single-trait QTLs have already been detected in the SLA region, and multivariate approaches have been used to exploit the correlations between the traits to obtain more information on their pattern: almost 500 measurements were recorded for backfat thickness (BFT1, BFT2), backfat weight (BFW) and leaf fat weight (LFW) but only about half that number for intramuscular fat content (IMF), affecting the detection. First, groups of traits were selected using a backward selection procedure: traits were selected based on their contribution to the linear combination of traits discriminating the putative QTL haplotypes. Three groups of traits could be distinguished based on successive discriminant analyses: external fat (BFT1, BFT2), internal fat (LFW, IMF) and BFW. At least four regions were distinguished, preferentially affecting one or the other group, with the SLA region always influencing all the traits. Meishan alleles decreased all trait values except IMF, confirming an opportunity for marker-assisted selection to improve meat quality with maintenance of carcass composition based on Meishan alleles.

The lepidopteran Bombyx mori is an insect of considerable scientific and economic importance. Recently, the B. mori circadian clock gene period has been molecularly characterized. We have transformed a B. mori strain with a construct encoding a period double-strand RNA in order to knock-down period gene expression. We observe that this post-transcriptional silencing produces a small but detectable disruption in the egg-hatching rhythm, as well as a reduction in egg-to-adult developmental time, without altering silk production parameters. Thus we show that both circadian and non-circadian phenotypes can be altered by changing per expression, and, at a practical level, these results suggest that per knock-down may provide a suitable strategy for improving the efficiency of rearing, without affecting silk productivity.

Tol1 is a DNA-based transposable element identified in the medaka fish Oryzias latipes and a member of the hAT (hobo/Activator/Tam3) transposable element family. Its mobility has already been demonstrated in the human and mouse, in addition to its original host species. This element is thus expected to be useful in a wide range of vertebrates as a genomic manipulation tool. Herein, we show that the Tol1 element can undergo excision in the African clawed frog Xenopus laevis, a major model organism for vertebrate genetics and developmental biology. An indicator plasmid carrying a Tol1 element was injected into 2- or 4-cell-stage embryos together with either a helper plasmid coding for the full-length Tol1 transposase or a modified helper plasmid yielding a truncated protein, and recovered from tailbud-stage embryos. Deletion of the Tol1 region of the indicator plasmid was observed in the experiment with the full-length transposase, and not in the other case. The deletion was associated with various footprint sequences at breakpoints, as frequently observed with many DNA-based transposable elements. These results indicate that the Tol1 element was excised from the indicator plasmid by catalysis of the transposase, and suggest that the Tol1 element is mobile in this frog species.

Knowledge of the genetic relatedness among individuals is essential in diverse research areas such as behavioural ecology, conservation biology, quantitative genetics and forensics. How to estimate relatedness accurately from genetic marker information has been explored recently by many methodological studies. In this investigation I propose a new likelihood method that uses the genotypes of a triad of individuals in estimating pairwise relatedness (r). The idea is to use a third individual as a control (reference) in estimating the r between two other individuals, thus reducing the chance of genes identical in state being mistakenly inferred as identical by descent. The new method allows for inbreeding and accounts for genotype errors in data. Analyses of both simulated and human microsatellite and SNP datasets show that the quality of r estimates (measured by the root mean squared error, RMSE) is generally improved substantially by the new triadic likelihood method (TL) over the dyadic likelihood method and five moment estimators. Simulations also show that genotyping errors/mutations, when ignored, result in underestimates of r for related dyads, and that incorporating a model of typing errors in the TL method improves r estimates for highly related dyads but impairs those for loosely related or unrelated dyads. The effects of inbreeding were also investigated through simulations. It is concluded that, because most dyads in a natural population are unrelated or only loosely related, the overall performance of the new triadic likelihood method is the best, offering r estimates with a RMSE that is substantially smaller than the five commonly used moment estimators and the dyadic likelihood method.

Muller's ratchet is an evolutionary process that has been implicated in the extinction of asexual species, the evolution of non-recombining genomes, such as the mitochondria, the degeneration of the Y chromosome, and the evolution of sex and recombination. Here we study the speed of Muller's ratchet in a spatially structured population which is subdivided into many small populations (demes) connected by migration, and distributed on a graph. We studied different types of networks: regular networks (similar to the stepping-stone model), small-world networks and completely random graphs. We show that at the onset of the small-world network – which is characterized by high local connectivity among the demes but low average path length – the speed of the ratchet starts to decrease dramatically. This result is independent of the number of demes considered, but is more pronounced the larger the network and the stronger the deleterious effect of mutations. Furthermore, although the ratchet slows down with increasing migration between demes, the observed decrease in speed is smaller in the stepping-stone model than in small-world networks. As migration rate increases, the structured populations approach, but never reach, the result in the corresponding panmictic population with the same number of individuals. Since small-world networks have been shown to describe well the real contact networks among people, we discuss our results in the light of the evolution of microbes and disease epidemics.

The importance of variance modelling is now widely known for the analysis of microarray data. In particular the power and accuracy of statistical tests for differential gene expressions are highly dependent on variance modelling. The aim of this paper is to use a structural model on the variances, which includes a condition effect and a random gene effect, and to propose a simple estimation procedure for these parameters by working on the empirical variances. The proposed variance model was compared with various methods on both real and simulated data. It proved to be more powerful than the gene-by-gene analysis and more robust to the number of false positives than the homogeneous variance model. It performed well compared with recently proposed approaches such as SAM and VarMixt even for a small number of replicates, and performed similarly to Limma. The main advantage of the structural model is that, thanks to the use of a linear mixed model on the logarithm of the variances, various factors of variation can easily be incorporated in the model, which is not the case for previously proposed empirical Bayes methods. It is also very fast to compute and is adapted to the comparison of more than two conditions.

Robertsonian (Rb) translocation is the largest source of chromosomal diversity in the western European house mouse (Mus musculus domesticus). Recently, the fusion Rb(7.17) was found in the chromosomal polymorphic zone of this subspecies in the north-east of the Iberian Peninsula. This fusion has not been reported in any other European population. Here we give data on the distribution and frequency of this mutation in this region. Results revealed that Rb(7.17) is restricted to a small geographic area, and that, in comparison with other fusions in this polymorphic zone, it occurs at low frequencies. We suggest some possible explanations for the distribution of this translocation.

The extent to which quantitative trait variability is caused by rare alleles maintained by mutation, versus intermediate-frequency alleles maintained by balancing selection, is an unsolved problem of evolutionary genetics. We describe the results of an experiment to examine the effects of selection on the mean and extent of inbreeding depression for early female fecundity in Drosophila melanogaster. Theory predicts that rare, partially recessive deleterious alleles should cause a much larger change in the effect of inbreeding than in the mean of the outbred population, with the change in inbreeding effect having an opposite sign to the change in mean. The present experiment fails to support this prediction, suggesting that intermediate-frequency alleles contribute substantially to genetic variation in early fecundity.

Phenotypic and genetic variation and covariation in developmental instability (DI) have been the subject of many debates. In this paper we develop and apply a statistical model in a Bayesian context to analyse different traits simultaneously in a multivariate model of DI. We apply the model to measurements of yellow spots on the front wing of the Speckled Wood butterfly (Pararge aegeria L.) in a full-sib breeding experiment. We estimated the posterior distribution of the broad-sense heritability of DI averaged across the five yellow spots, which had a median of 0·19 and a 95% credibility interval ranging between 0·04 and 0·64. Phenotypic and genetic correlations in DI could not be estimated accurately with the present sample size. Yellow spots 4 and 5 appeared to show some degree of developmental integration. The importance of this model and its possible extensions are discussed.

Thirty-one genomic SSR markers with a M13 tail attached were used to assess the genetic diversity of the peanut mini core collection. The M13-tailed method was effective in discriminating almost all the cultivated and wild accessions. A total of 477 alleles were detected with an average of 15·4 alleles per locus. The mean polymorphic information content (PIC) score was 0·687. The cultivated peanut (Arachis hypogaea L.) mini core produced a total of 312 alleles with an average of 10·1 alleles per locus. A neighbour-joining tree was constructed to determine the interspecific and intraspecific relationships in this data set. Almost all the peanut accessions in this data set classified into subspecies and botanical varieties such as subsp. hypogaea var. hypogaea, subsp. fastigiata var. fastigiata, and subsp. fastigiata var. vulgaris clustered with other accessions with the same classification, which lends further support to their current taxonomy. Alleles were sequenced from one of the SSR markers used in this study, which demonstrated that the repeat motif is conserved when transferring the marker across species borders. This study allowed the examination of the diversity and phylogenetic relationships in the peanut mini core which has not been previously reported.

Bread wheat (Triticum aestivum L.) exhibits very narrow genetic diversity and hence there is high relatedness among cultivated varieties. However, a population generated from an intervarietal cross, with the parents differing in a large number of traits, could lead to the generation of QTL maps which will be useful in practice. In this report a genetic linkage map of wheat is constructed using a cross between two Indian bread wheat varieties: Sonalika and Kalyansona. The linkage map consisted of 236 markers and spanned a distance of 3639 cM, with 1211·2 cM for the A genome, 1669·2 cM for the B genome, 192·4 cM for the D genome and 566·2 cM for unassigned groups. Linkage analysis defined 37 linkage groups of which 24 were assigned to 17 chromosomes. The genetic map was used to identify QTLs by composite internal mapping (CIM) for three metric traits, viz. culm length (CL), flag leaf length (FLL) and flag leaf breadth (FLB). Of 25 QTLs identified in this study, 15 have not been reported previously. Multitrait CIM (MCIM) analysis was carried out for traits that were significantly correlated such as FLB–FLL and CL–FLB–FLL. Detection of a large number of QTLs for the three traits analysed suggests that in parent cultivars that are not too diverse, the differences at genetic level detected as polymorphisms may be mostly associated with QTLs for the observed differences.

A key question for the implementation of marker-assisted selection (MAS) using markers in linkage disequilibrium with quantitative trait loci (QTLs) is how many markers surrounding each QTL should be used to ensure the marker or marker haplotypes are in sufficient linkage disequilibrium (LD) with the QTL. In this paper we compare the accuracy of MAS using either single markers or marker haplotypes in an Angus cattle data set consisting of 9323 genome-wide single nucleotide polymorphisms (SNPs) genotyped in 379 Angus cattle. The extent of LD in the data set was such that the average marker–marker r2 was 0·2 at 200 kb. The accuracy of MAS increased as the number of markers in the haplotype surrounding the QTL increased, although only when the number of markers in the haplotype was 4 or greater did the accuracy exceed that achieved when the SNP in the highest LD with the QTL was used. A large number of phenotypic records (>1000) were required to accurately estimate the effects of the haplotypes.

Whether there are different genes involved in response to different environmental signals and how these genes interact to determine the final expression of the trait are of fundamental importance in agricultural and biological research. We present a statistical framework for mapping environment-induced genes (or quantitative trait loci, QTLs) of major effects on the expression of a trait that respond to changing environments. This framework is constructed with a maximum-likelihood-based mixture model, in which the mean and covariance structure of environment-induced responses is modelled. The means for responses to continuous environmental states, referred to as reaction norms, are approximated for different QTL genotypes by mathematical equations that were derived from fundamental biological principles or based on statistical goodness-of-fit to observational data. The residual covariance between different environmental states was modelled by autoregressive processes. Such an approach to studying the genetic control of reaction norms can be expected to be advantageous over traditional mapping approaches in which no biological principles and statistical structures are considered. We demonstrate the analytical procedure and power of this approach by modelling the photosynthetic rate process as a function of temperature and light irradiance. Our approach allows for testing how a QTL affects the reaction norm of photosynthetic rate to a specific environment and whether there exist different QTLs to mediate photosynthetic responses to temperature and light irradiance, respectively.